scholarly journals Resonance Image Enhancement using Hybrid Center Weighted Median Filter and Bacteria Foraging Optimization

2020 ◽  
Vol 8 (5) ◽  
pp. 2740-2745

Magnetic Resonance Image (MRI) is the best imaging technique employed nowadays for diagnosing brain tumour in the initial stage. This paper recommends an unique method for the brain MR image enhancement, that is centred on the Hybrid Center Weighted Median (HCWM) filter and Bacteria Foraging Optimization (BFO). The MR image for this research is obtained from the online and it is pre-processed to remove all the film artifacts. After that the high frequency components are eliminated from the MR brain image by means of a newly proposed HCWM filter. HCWM Filter is the hybrid filter derived by combining the Center Weighted Median Filter and the Weiner Filter. The swarm-based intelligence algorithm called the bacteria foraging optimization is used to predict the weights of the filter dynamically. The performance of the proposed filtering approach is evaluated with the other available filtering methods.

2021 ◽  
Vol 27 (5) ◽  
pp. 356-363
Author(s):  
Hyun-Bin Lim ◽  
Eung-su Kim ◽  
Duk-Man Lee ◽  
Hee-Soo Kim ◽  
Soon-Yong Park

Author(s):  
N. Rajalakshmi ◽  
K. Narayanan ◽  
P. Amudhavalli

<p>Preliminary diagnosing of MRI images from the hospital cannot be relied on because of the chances of occurrence of artifacts resulting in degraded quality of image, while others may be confused with pathology. Obtained MRI image usually contains limited artifacts. It becomes complex one for doctors in analyzing them. By increasing the contrast of an image, it will be easy to analyze. In order to find the tumor part efficiently MRI brain image should be enhanced properly. The image enhancement methods mainly improve the visual appearance of MRI images. The goal of denoising is to remove the noise, which may corrupt an image during its acquisition or transmission, while retaining its quality. In this paper effectiveness of seven denoising algorithms viz. median filter, wiener filter, wavelet filter, wavelet based wiener, NLM, wavelet based NLM, proposed wavelet based weighted median filter(WMF) using MRI images in the presence of additive white Gaussian noise is compared. The experimental results are analyzed in terms of various image quality metrics.</p>


1984 ◽  
Vol 27 (8) ◽  
pp. 807-818 ◽  
Author(s):  
D. R. K. Brownrigg

1991 ◽  
Vol 16 (3) ◽  
pp. 168 ◽  
Author(s):  
Akira Asano ◽  
Kazuyoshi Itoh ◽  
Yoshiki Ichioka

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